Instalación de cámaras

En articulación con WCS-CARDER

mapa
cámaras
SFF Otun-Quimbaya
52 trampas cámara instaladas
Authors
Affiliations

Diego Lizcano

IUCN/SSC Tapir Specialist Group (TSG)

Wildlife Conservation Society (WCS)

Juliana Vélez-Gómez

IUCN/SSC Tapir Specialist Group (TSG)

Leonor Valenzuela

Wildlife Conservation Society (WCS)

Jackeline Rivera-Gómez

CARDER

Robinson Galindo-Tarazona

SFF Otún Quimbaya

María Girleza Ramírez-González

SFF Otún Quimbaya

Juan Camilo Mantilla-Castaño

SFF Otún Quimbaya

Published

December 10, 2025

Diseño de muestreo con cámaras

Elaboramos una red de posibles puntos de instalación de camaras en Risaralda, en conjunto con la CARDER y WCS. Esta red de puntos fue proyectada para cubrir tambien el area del SFF Otun-Quimbaya y el PNN Los Nevados como una cuadricula con separacion de 500 metros.

Code
library(grateful) # Facilitate Citation of R Packages
library(readxl) # Read Excel Files
library(DT) # A Wrapper of the JavaScript Library 'DataTables'
library(sf) # Simple Features for R
library(mapview) # Interactive Viewing of Spatial Data in R
# library(maps) # Draw Geographical Maps
library(tmap) # Thematic Maps
library(terra) # Spatial Data Analysis
library(elevatr) # Access Elevation Data from Various APIs
library(glue) # easy paste
library(tidyverse) # Easily Install and Load the 'Tidyverse'
Code
##| column: screen-inset-shaded # wide


cameras <- read_sf("C:/CodigoR/screwworm_mountain_tapir/data/cameras.csv")

# Convert to a Spatial Object (sf)
# CRS 4326 is standard WGS84 for Google Earth
cameras_sf <- st_as_sf(cameras, coords = c("Longitude", "Latitude"), crs = 4326)

puntos_500m <- read_sf("C:/CodigoR/screwworm_mountain_tapir/data/shp/puntos_camaras_500m.geojson")

SFF_Otun_Quimbaya <- read_sf("C:/CodigoR/screwworm_mountain_tapir/data/shp/WDPA_WDOECM_Jan2026_Public_303548_shp-polygons.shp")[,5:9]

PNN_Nevados <- read_sf("C:/CodigoR/screwworm_mountain_tapir/data/shp/WDPA_WDOECM_Jan2026_Public_147_shp-polygons.shp")[,5:9]

PR_Ucumari <- read_sf("C:/CodigoR/screwworm_mountain_tapir/data/shp/WDPA_WDOECM_Jan2026_Public_555555791_shp-polygons.shp")[,5:9]


#corine <- read_sf("C:/CodigoR/screwworm_mountain_tapir/data/shp/ECOSISTEMAS_18062025.gpkg") |> st_transform(4326) 

# 2. Using the extent of another object
#target_bbox <- st_bbox(puntos_500m) |> st_buffer(dist = 0.5) 
#cropped_corine <- st_crop(corine, target_bbox)
# remove corine large from memory
# rm(corine)

croped_corine <- read_sf("C:/CodigoR/screwworm_mountain_tapir/data/shp/corine_cortado.gpkg") |> st_transform(4326) 

# get elevation map
# elevation_18 <- rast(get_elev_raster(cameras_sf, z = 12)) #z =1-14
# bb <-  st_as_sfc(st_bbox(elevation_17)) # make bounding box 




# extract covs using points and add to _sites
# covs_Col_18_sites <- cbind(Col_18_sites, terra::extract(elevation_18, Col_18_sites))
# covs_Col_17_sites <- cbind(Col_17_sites, terra::extract(elevation_17, Col_17_sites))


# get which are in and out
cameras_sf$in_AP = st_intersects(cameras_sf, SFF_Otun_Quimbaya, sparse = FALSE)
# covs_Col_17_sites$in_AP = st_intersects(covs_Col_17_sites, AP_Yasuni, sparse = FALSE)


# make a map
# mapview (cropped_corine, alpha=0.5) + 
#   mapview (elevation_18, alpha=0.5) + 
#   mapview (AP_Ucumari, color = "lightgreen", col.regions = "green", alpha = 0.5) +
#   mapview (AP_Nevados, color = "lightgreen", col.regions = "green", alpha = 0.5) +
#   mapview (AP_Otun, color = "green", col.regions = "green", alpha = 0.5) +
#   mapview(puntos_500m)

#  mapview (cameras_sf, zcol = "in_AP", col.regions =c("red","blue"), burst = TRUE) 

tmap_mode("view")
#> ℹ tmap modes "plot" - "view"
#> ℹ toggle with `tmap::ttm()`
tm_shape(PR_Ucumari) +
  tm_polygons(
    #fill = "dwelling_value",
    col = "green",
    fill = "lightgreen",
    fill_alpha = 0.5) +
tm_shape(PNN_Nevados) +
  tm_polygons(
    #fill = "dwelling_value",
    col = "green",
    #fill = "lightgreen",
    fill_alpha = 0.5) +
  tm_shape(SFF_Otun_Quimbaya) +
  tm_polygons(
    #fill = "dwelling_value",
    col = "green",
    fill = "lightgreen",
    fill_alpha = 0.5) +
tm_shape(puntos_500m) +
      tm_dots(
         size = 0.3,
         #lwd = 1,
         fill = "red",
         col = "black",
         fill_alpha = 0.5
         ) +
    tm_basemap("Esri.WorldTopoMap")+# "CartoDB.Voyager")+# "Stadia.StamenTerrain") + 
    tm_minimap(position = c("left", "top"),
               height = 4,
               width = 5)

Mapa de localización de la red de puntos. Cuadricula de 500 metros

Estratificacion por coberturas

Se descargó el mapa de coberturas de MapBiomas y se recortó a la zona proyectada de puntos para contar con camaras en todas las coberturas.

Distribución proporcional

Bosque 2,558,147 2,558,147/5,814,440 = 0.4400 0.4400 × 100 44 Agricultura 3,124,230 3,124,230/5,814,440 = 0.5373 0.5373 × 100 54 Pino Plantado 132,063 132,063/5,814,440 = 0.0227 0.0227 × 100 2 TOTAL 5,814,440 1.0000 100

Minimum = 10 points per class Remaining = 100 - (3 × 10) = 70 points

Bosque: 10 + (70 × 0.4400) = 10 + 31 = 41 points Agricultura: 10 + (70 × 0.5373) = 10 + 38 = 48 points Pino: 10 + (70 × 0.0227) = 10 + 2 = 12 points (use minimum)

Camaras Instaladas

En diciembre 2025 se instalaron 52 camaras

Instalación de cámara

Instalación de cámara

Toma de punto de GPS

Toma de punto de GPS

Instalación de cámara

Instalación de cámara

Instalación de cámara

Instalación de cámara
Code
library(leaflet)
library(leafpop)

#fotos <- cameras_sf$foto_url

mapview(PR_Ucumari, 
        color = "green", #col.regions = NULL,
        map.types = "Esri.WorldImagery",
        alpha=0.75) +
mapview(PNN_Nevados, 
        color = "green", col.regions = "lightgreen",
        #map.types = "Esri.WorldImagery",
        alpha=0.75) +
mapview(SFF_Otun_Quimbaya, 
        color = "green", col.regions = "green",
        #map.types = "Esri.WorldImagery",
        alpha=0.75) +
mapview(cameras_sf,
        zcol="proyecto",
        popup = popupTable(cameras_sf,
                                      zcol = c("instalador",
                                               "proyecto",
                                               "Ecosistema"))
        #zcol = c("instalador", "proyecto", "Ecosistema")
        # popup = popupImage(fotos, 
        #                   src = "remote",
        #                   embed = TRUE)
 )

Localización de las camaras instaladas en Diciembre 2025. Instituciones participantes: CARDER, WCS, TSG, PNN

Package Citation

Code
pkgs <- cite_packages(output = "paragraph", pkgs="Session", out.dir = ".")
# knitr::kable(pkgs)
pkgs

We used R v. 4.4.2 (R Core Team 2024) and the following R packages: DT v. 0.34.0 (Xie et al. 2025), elevatr v. 0.99.0 (Hollister et al. 2023), glue v. 1.8.0 (Hester and Bryan 2024), leaflet v. 2.2.3 (Cheng et al. 2025), leafpop v. 0.1.0 (Appelhans and Detsch 2021), mapview v. 2.11.4 (Appelhans et al. 2025), sf v. 1.0.21 (Pebesma 2018; Pebesma and Bivand 2023), terra v. 1.8.70 (Hijmans 2025), tidyverse v. 2.0.0 (Wickham et al. 2019), tmap v. 4.2 (Tennekes 2018).

Sesion info

Code
print(sessionInfo(), locale = FALSE)
R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 10 x64 (build 19045)

Matrix products: default


attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] leafpop_0.1.0   leaflet_2.2.3   lubridate_1.9.4 forcats_1.0.0  
 [5] stringr_1.5.2   dplyr_1.1.4     purrr_1.1.0     readr_2.1.5    
 [9] tidyr_1.3.1     tibble_3.2.1    ggplot2_4.0.1   tidyverse_2.0.0
[13] glue_1.8.0      elevatr_0.99.0  terra_1.8-70    tmap_4.2       
[17] mapview_2.11.4  sf_1.0-21       DT_0.34.0       readxl_1.4.3   
[21] grateful_0.3.0 

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.1        farver_2.1.2            S7_0.2.1               
 [4] fastmap_1.2.0           leaflegend_1.2.1        XML_3.99-0.18          
 [7] digest_0.6.37           timechange_0.3.0        lifecycle_1.0.4        
[10] magrittr_2.0.3          compiler_4.4.2          rlang_1.1.6            
[13] tools_4.4.2             yaml_2.3.10             data.table_1.17.8      
[16] knitr_1.50              brew_1.0-10             htmlwidgets_1.6.4      
[19] sp_2.2-0                classInt_0.4-11         RColorBrewer_1.1-3     
[22] abind_1.4-8             KernSmooth_2.23-24      withr_3.0.2            
[25] leafsync_0.1.0          grid_4.4.2              stats4_4.4.2           
[28] cols4all_0.8-1          e1071_1.7-16            leafem_0.2.4           
[31] colorspace_2.1-1        spacesXYZ_1.6-0         progressr_0.15.0       
[34] scales_1.4.0            dichromat_2.0-0.1       cli_3.6.5              
[37] rmarkdown_2.30          generics_0.1.3          rstudioapi_0.17.1      
[40] tzdb_0.4.0              tmaptools_3.3           DBI_1.2.3              
[43] proxy_0.4-27            stars_0.6-8             parallel_4.4.2         
[46] s2_1.1.9                cellranger_1.1.0        base64enc_0.1-3        
[49] vctrs_0.6.5             jsonlite_2.0.0          hms_1.1.3              
[52] systemfonts_1.1.0       crosstalk_1.2.1         jquerylib_0.1.4        
[55] units_0.8-7             maptiles_0.10.0         lwgeom_0.2-14          
[58] leaflet.providers_2.0.0 codetools_0.2-20        stringi_1.8.4          
[61] gtable_0.3.6            raster_3.6-32           logger_0.4.0           
[64] pillar_1.11.1           htmltools_0.5.8.1       satellite_1.0.5        
[67] R6_2.6.1                wk_0.9.4                microbenchmark_1.5.0   
[70] evaluate_1.0.4          lattice_0.22-6          png_0.1-8              
[73] class_7.3-22            uuid_1.2-1              Rcpp_1.1.0             
[76] svglite_2.1.3           xfun_0.52               pkgconfig_2.0.3        

References

Appelhans, Tim, and Florian Detsch. 2021. leafpop: Include Tables, Images and Graphs in Leaflet Pop-Ups. https://CRAN.R-project.org/package=leafpop.
Appelhans, Tim, Florian Detsch, Christoph Reudenbach, and Stefan Woellauer. 2025. mapview: Interactive Viewing of Spatial Data in r. https://CRAN.R-project.org/package=mapview.
Cheng, Joe, Barret Schloerke, Bhaskar Karambelkar, Yihui Xie, and Garrick Aden-Buie. 2025. leaflet: Create Interactive Web Maps with the JavaScript Leaflet Library. https://CRAN.R-project.org/package=leaflet.
Hester, Jim, and Jennifer Bryan. 2024. glue: Interpreted String Literals. https://CRAN.R-project.org/package=glue.
Hijmans, Robert J. 2025. terra: Spatial Data Analysis. https://CRAN.R-project.org/package=terra.
Hollister, Jeffrey, Tarak Shah, Jakub Nowosad, Alec L. Robitaille, Marcus W. Beck, and Mike Johnson. 2023. elevatr: Access Elevation Data from Various APIs. https://doi.org/10.5281/zenodo.8335450.
Pebesma, Edzer. 2018. Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal 10 (1): 439–46. https://doi.org/10.32614/RJ-2018-009.
Pebesma, Edzer, and Roger Bivand. 2023. Spatial Data Science: With applications in R. Chapman and Hall/CRC. https://doi.org/10.1201/9780429459016.
R Core Team. 2024. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Tennekes, Martijn. 2018. tmap: Thematic Maps in R.” Journal of Statistical Software 84 (6): 1–39. https://doi.org/10.18637/jss.v084.i06.
Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.
Xie, Yihui, Joe Cheng, Xianying Tan, and Garrick Aden-Buie. 2025. DT: A Wrapper of the JavaScript Library DataTables. https://CRAN.R-project.org/package=DT.

Reuse

Citation

BibTeX citation:
@online{lizcano2025,
  author = {Lizcano, Diego and Vélez-Gómez, Juliana and Valenzuela,
    Leonor and Rivera-Gómez, Jackeline and Galindo-Tarazona, Robinson
    and Girleza Ramírez-González, María and Camilo Mantilla-Castaño,
    Juan},
  title = {Instalación de Cámaras},
  date = {2025-12-10},
  url = {https://dlizcano.github.io/screwworm_mountain_tapir/blog/2025-12-10-instalacion/},
  langid = {en}
}
For attribution, please cite this work as:
Lizcano, Diego, Juliana Vélez-Gómez, Leonor Valenzuela, Jackeline Rivera-Gómez, Robinson Galindo-Tarazona, María Girleza Ramírez-González, and Juan Camilo Mantilla-Castaño. 2025. “Instalación de Cámaras.” December 10, 2025. https://dlizcano.github.io/screwworm_mountain_tapir/blog/2025-12-10-instalacion/.